Backscattering Coefficient Bbp Research Articles

Improved multivariable algorithms for estimating oceanic particulate organic carbon concentration from optical backscattering and chlorophyll-a measurements

The capability to estimate the oceanic particulate organic carbon concentration (POC) from optical measurements is crucial for assessing the dynamics of this carbon reservoir and the capacity of the biological pump to sequester atmospheric carbon dioxide in the deep ocean. Optical approaches are routinely used to estimate oceanic POC from the spectral particulate backscattering coefficient bbp, either directly (e.g., with backscattering sensors on underwater platforms like BGC-Argo floats) or indirectly (e.g., with satellite remote sensing). However, the reliability of algorithms which relate POC to bbp is typically limited due to the complexity of interactions between light and natural assemblages of marine particles, which depend on variations in particle concentration, composition, and size distribution. This study expands on our previous work by analysis of an extended field dataset created with judicious data inclusion criteria with the aim to provide POC algorithms for multiple light wavelengths of measured bbp, which can be useful for applications with in situ optical sensors as well as above-water active or passive measurement systems. We describe an improved empirical multivariable approach to estimate POC from simultaneous measurements of bbp and chlorophyll-a concentration (Chla) to better account for the effects of variable particle composition on the relationship between POC and bbp. The multivariable regression models are formulated using a relatively large dataset of coincident measurements of POC, bbp, and Chla, including surface and subsurface data from the Atlantic, Pacific, Arctic, and Southern Oceans. We show that the multivariable algorithm provides reduced uncertainty of estimated POC across diverse marine environments when compared with a traditional univariate algorithm based on only bbp. We also propose an improved formulation of univariate algorithm based on bbp alone. Finally, we examine performance of several algorithms to estimate POC using our dataset as well as a dataset consisting of optical measurements from BGC-Argo floats and traditional POC measurements collected during a coincident research cruise in the Atlantic Ocean.

Validation protocol for the evaluation of space-borne lidar particulate back-scattering coefficient bbp

Introduction: Space-borne lidar measurements from sensors such as CALIOP were recently used to retrieve the particulate back-scattering coefficient, bbp, in the upper ocean layers at a global scale and those observations have a strong potential for the future of ocean color with depth-resolved observations thereby complementing the conventional ocean color remote sensed observations as well as overcoming for some of its limitations. It is critical to evaluate and validate the space-borne lidar measurements for ocean applications as CALIOP was not originally designed for ocean applications. Few validation exercises of CALIOP were published and each exercise designed its own validation protocol. We propose here an objective validation protocol that could be applied to any current and future space-borne lidars for ocean applications.Methods: We, first, evaluated published validation protocols for CALIOP bbp product. Two published validation schemes were evaluated in our study, by using in-situ measurements from the BGC-Argo floats. These studies were either limited to day- or nighttime, or by the years used or by the geographical extent. We extended the match-up exercise to day-and nighttime observations and for the period 2010–2017 globally. We studied the impact of the time and distance differences between the in-situ measurements and the CALIOP footprint through a sensitivities study. Twenty combinations of distance (from 9-km to 50-km) and time (from 9 h to 16 days) differences were tested.Results & Discussion: A statistical score was used to objectively selecting the best optimal timedistance windows, leading to the best compromise in term of number of matchups and low errors in the CALIOP product. We propose to use either a 24 h/9 km or 24 h/15 km window for the evaluation of space-borne lidar oceanic products.

A dataset of remote sensing-based inherent optical properties of Hulun Lake from 2016 to 2020

Hulun Lake, the largest steppe lake in the high latitude semi-arid region of inland China, holds great significance for grassland production and steppe-lake ecosystem. The absorption coefficient of water constitutes is indicative of the optically active components in water, thus conducive to estimating the optically active substances and other related bio-optical parameters of waters. In this study, we used the quasi-analytical algorithm (QAA), a QAA-750E absorption coefficient inversion algorithm suitable for inland waters. Based on Sentinel-3/OLCI remote sensing reflectance data, we produced a dataset of monthly mean phytoplankton absorption coefficient aph(675)and backscattering coefficient bbp(560) of Hulun Lake during 2016-2020. Validation analysis results show that the model-derived b_bp (560) has an R2 value of 0.59, RMSE of 0.55, and MRD of 0.54 (N = 15), indicating a high level of reliability of the dataset. The dataset is expected to offer data support for water quality monitoring and ecological environment protection of Hulun Lake.

Shipborne oceanic high-spectral-resolution lidar for accurate estimation of seawater depth-resolved optical properties

Lidar techniques present a distinctive ability to resolve vertical structure of optical properties within the upper water column at both day- and night-time. However, accuracy challenges remain for existing lidar instruments due to the ill-posed nature of elastic backscatter lidar retrievals and multiple scattering. Here we demonstrate the high performance of, to the best of our knowledge, the first shipborne oceanic high-spectral-resolution lidar (HSRL) and illustrate a multiple scattering correction algorithm to rigorously address the above challenges in estimating the depth-resolved diffuse attenuation coefficient Kd and the particulate backscattering coefficient bbp at 532 nm. HSRL data were collected during day- and night-time within the coastal areas of East China Sea and South China Sea, which are connected by the Taiwan Strait. Results include vertical profiles from open ocean waters to moderate turbid waters and first lidar continuous observation of diel vertical distribution of thin layers at a fixed station. The root-mean-square relative differences between the HSRL and coincident in situ measurements are 5.6% and 9.1% for Kd and bbp, respectively, corresponding to an improvement of 2.7–13.5 and 4.9–44.1 times, respectively, with respect to elastic backscatter lidar methods. Shipborne oceanic HSRLs with high performance are expected to be of paramount importance for the construction of 3D map of ocean ecosystem.

A Multivariable Empirical Algorithm for Estimating Particulate Organic Carbon Concentration in Marine Environments From Optical Backscattering and Chlorophyll-a Measurements

Accurate estimates of the oceanic particulate organic carbon concentration (POC) from optical measurements have remained challenging because interactions between light and natural assemblages of marine particles are complex, depending on particle concentration, composition, and size distribution. In particular, the applicability of a single relationship between POC and the spectral particulate backscattering coefficient bbp(λ) across diverse oceanic environments is subject to high uncertainties because of the variable nature of particulate assemblages. These relationships have nevertheless been widely used to estimate oceanic POC using, for example, in situ measurements of bbp from Biogeochemical (BGC)-Argo floats. Despite these challenges, such an in situbased approach to estimate POC remains scientifically attractive in view of the expanding global-scale observations with the BGC-Argo array of profiling floats equipped with optical sensors. In the current study, we describe an improved empirical approach to estimate POC which takes advantage of simultaneous measurements of bbp and chlorophyll-a fluorescence to better account for the effects of variable particle composition on the relationship between POC and bbp. We formulated multivariable regression models using a dataset of field measurements of POC, bbp, and chlorophyll-a concentration (Chla), including surface and subsurface water samples from the Atlantic, Pacific, Arctic, and Southern Oceans. The analysis of this dataset of diverse seawater samples demonstrates that the use of bbp and an additional independent variable related to particle composition involving both bbp and Chla leads to notable improvements in POC estimations compared with a typical univariate regression model based on bbp alone. These multivariable algorithms are expected to be particularly useful for estimating POC with measurements from autonomous BGC-Argo floats operating in diverse oceanic environments. We demonstrate example results from the multivariable algorithm applied to depth-resolved vertical measurements from BGC-Argo floats surveying the Labrador Sea.

Characterization of suspended particulate matter in contrasting coastal marine environments with angle-resolved polarized light scattering measurements.

Optical proxies based on light scattering measurements have potential to improve the study and monitoring of aquatic environments. In this study, we evaluated several optical proxies for characterization of particle mass concentration, composition, and size distribution of suspended particulate matter from two contrasting coastal marine environments. We expanded upon our previous study of Southern California coastal waters, which generally contained high proportions of organic particles, by conducting angle-resolved polarized light scattering measurements in predominantly turbid and inorganic-particle dominated Arctic coastal waters near Prudhoe Bay, Alaska. We observed that the particulate backscattering coefficient bbp was the most effective proxy for the mass concentration of suspended particulate matter (SPM) when compared with particulate scattering and attenuation coefficients bp and cp. Improvements were seen with bbp as a proxy for the concentration of particulate organic carbon (POC), although only if particulate assemblages were previously classified in terms of particle composition. We found that the ratio of polarized-light scattering measurements at 110º and 18º was superior in performance as a proxy for the composition parameter POC/SPM in comparison to the particulate backscattering ratio bbp/bp. The maximum value of the degree of linear polarization DoLPp,max observed within the range of scattering angles 89°-106° was found to provide a reasonably good proxy for a particle size parameter (i.e., 90th percentile of particle volume distribution) which characterizes the proportions of small- and large-sized particles. These findings can inform the development of polarized light scattering sensors to enhance the capabilities of autonomous platforms.

Reconstruction of salinity data in the Sea of Azov from satellite measurements in the visible spectrum

A method based on the use of statistical procedures and three-dimensional hydrodinamical simulation with assimilation of remote sensing data to obtain regular information on the temperature and salinity of the Sea of the Azov is proposed. We used the in situ measurements of temperature and salinity for the period 19132012 and the observations data from MODIS-Aqua/Terra instruments regularly passing over the Sea of the Azov and the simulation results of three-dimensional hydrodynamic Princeton Ocean Model. The possibility of the operative recovery of salinity values is based on regression statistics on the bio-optical characteristics remote sensing reflectance band ratio index34 = RRS(531)/RRS(488) and particulate backscattering coefficient bbp(555).

Inherent Optical Properties in Lake Taihu Derived from VIIRS Satellite Observations

Using in situ remote sensing reflectance and inherent optical property (IOP) measurements, a near-infrared (NIR)-based IOP algorithm is developed and tuned for Lake Taihu, in order to derive the particle backscattering coefficient bbp(λ), total absorption coefficient at(λ), dissolved and detrital absorption coefficient adg(λ), and phytoplankton absorption coefficient aph(λ), with satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). The IOP algorithm for Lake Taihu has a reasonably good accuracy. In fact, the determination coefficients between the retrieved and in situ IOPs are 0.772, 0.638, and 0.487 for at(λ), adg(λ), and aph(λ), respectively. The IOP products in Lake Taihu that have been derived from VIIRS-SNPP observations show significant spatial and temporal variations. Southern Lake Taihu features enhanced bbp(λ) and adg(λ), while northern Lake Taihu shows higher aph(λ). The seasonal and interannual variability of adg(λ) and bbp(λ) in Lake Taihu is quantified and characterized with the highest bbp(λ) and adg(λ) in the winter, and the lowest in the summer. In the winter, bbp(443) and adg(443) can reach over ~1.5 and ~5.0 m−1, respectively, while they are ~0.5–1.0 and ~2.0 m−1 in the summer. This study shows that in Lake Taihu adg(λ) is the most significant IOP, while aph(λ) is the least in terms of the IOP values and contributions to remote sensing reflectance. The highest bbp(λ) and adg(λ) occurred in the winter between 2017–2018, and the lowest bbp(λ) and adg(λ) occurred in the summer of 2014. In comparison, the seasonal and interannual variability of mean aph(λ) for Lake Taihu is less significant, even though enhanced seasonal and interannual variability can be found in some parts of Lake Taihu, such as in the northern Lake Taihu region.

Inferring and Removing a Spurious Response in the Optical Backscattering Signal from an Autonomous Profiling Float

AbstractDevelopment of autonomous profiling floats, allowing for long-term continuous measurement of bio-optical variables, promises to significantly increase our knowledge of the variability of the particulate optical backscattering coefficient bbp in marine environments. However, because autonomous floats are designed for unattended data collection and only rarely are recovered for analysis of the condition of the sensors in situ, the quality-control analysis of float data streams is of paramount importance in both a particular dataset and the larger understanding of the response of sensors over the lifetime of the floats. Anomalous data from a backscattering sensor (MCOMS) mounted on autonomous profiling floats are reported here. The observed sensor behavior, which presents itself as significant differences in the values observed at the parking depth between profiles, caused by a steady increase in the signal during the profiling time, is neither common to all sensors nor can it be a function of changes in the particle population. A simple quality-control procedure that is able to detect this spurious sensor response is proposed. Further characterization of this effect will require laboratory experimentation under controlled conditions of temperature and pressure.

Deriving Total Suspended Matter Concentration from the Near-Infrared-Based Inherent Optical Properties over Turbid Waters: A Case Study in Lake Taihu

Normalized water-leaving radiance spectra nLw(λ), particle backscattering coefficients bbp(λ) in the near-infrared (NIR) wavelengths, and total suspended matter (TSM) concentrations over turbid waters are analytically correlated. To demonstrate the use of bbp(λ) in the NIR wavelengths in coastal and inland waters, we used in situ optics and TSM data to develop two TSM algorithms from measurements of the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) using backscattering coefficients at the two NIR bands bbp(745) and bbp(862) for Lake Taihu. The correlation coefficients between the modeled TSM concentrations from bbp(745) and bbp(862) and the in situ TSM are 0.93 and 0.92, respectively. A different in situ dataset acquired between 2012 and 2016 for Lake Taihu was used to validate the performance of the NIR TSM algorithms for VIIRS-SNPP observations. TSM concentrations derived from VIIRS-SNPP observations with these two NIR bbp(λ)-based TSM algorithms matched well with in situ TSM concentrations in Lake Taihu between 2012 and 2016. The normalized root mean square errors (NRMSEs) for the two NIR algorithms are 0.234 and 0.226, respectively. The two NIR-based TSM algorithms are used to compute the satellite-derived TSM concentrations to study the seasonal and interannual variability of the TSM concentration in Lake Taihu between 2012 and 2016. In fact, the NIR-based TSM algorithms are analytically based with minimal in situ data to tune the coefficients. They are not sensitive to the possible nLw(λ) saturation in the visible bands for highly turbid waters, and have the potential to be used for estimation of TSM concentrations in turbid waters with similar NIR nLw(λ) spectra as those in Lake Taihu.

Characterization of Particle Backscattering of Global Highly Turbid Waters From VIIRS Ocean Color Observations

AbstractNormalized water‐leaving radiance spectra nLw(λ) at the near‐infrared (NIR) from five years of observations (2012–2016) with the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar‐orbiting Partnership (SNPP) are used to derive the particle backscattering coefficients bbp(λ) for global highly turbid coastal and inland waters. Based on the fact that the absorption coefficient of sea water aw(λ) is generally much larger than those of the other constituents aiop(λ) at the NIR wavelengths in coastal and inland waters, an NIR‐based bbp(λ) algorithm for turbid coastal and inland waters has been developed and used in this study. This algorithm can be safely used for highly turbid waters with nLw(745) and nLw(862) < ∼6 and ∼4 mW cm−2 μm−1 sr−1, respectively. Seasonal and interannual variations of bbp(λ) in China's east coastal region, the Amazon River Estuary, the La Plata River Estuary, the Meghna River Estuary, the Atchafalaya River Estuary, and Lake Taihu are characterized and quantified. The coefficient bbp(λ) can reach over ∼3–4 m−1 in the Amazon River Estuary and China's east coastal region. The Amazon River Estuary is identified as the most turbid region in the global ocean in terms of bbp(λ) magnitude. bbp(λ) spectra in these five highly turbid regions are also seasonal‐dependent and regional‐dependent. In the highly turbid waters of China's east coastal region and the Amazon River Estuary, bbp(λ) generally increases in wavelength from 410 to 862 nm, while it decreases in the La Plata River Estuary and Atchafalaya River Estuary. This is attributed to the different particle size distributions in these waters. The geophysical implication of the bbp(λ) spectral curvatures for different waters is discussed. To improve global bbp(λ) for both open oceans and coastal turbid waters, a new combined NIR‐based and Quasi‐Analytical Algorithm (QAA)‐based bbp(λ) algorithm is proposed and demonstrated.

Retrieval of ocean subsurface particulate backscattering coefficient from space-borne CALIOP lidar measurements.

A new approach has been proposed to determine ocean subsurface particulate backscattering coefficient bbp from CALIOP 30° off-nadir lidar measurements. The new method also provides estimates of the particle volume scattering function at the 180° scattering angle. The CALIOP based layer-integrated lidar backscatter and particulate backscattering coefficients are compared with the results obtained from MODIS ocean color measurements. The comparison analysis shows that ocean subsurface lidar backscatter and particulate backscattering coefficient bbp can be accurately obtained from CALIOP lidar measurements, thereby supporting the use of space-borne lidar measurements for ocean subsurface studies.

Simple statistical formulas for estimating biogeochemical properties of suspended particulate matter in the southern Baltic Sea potentially useful for optical remote sensing applications

Simple statistical formulas for estimating various biogeochemical properties of suspended particulate matter in the southern Baltic Sea are presented in this paper. These include formulas for estimating mass concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate organic carbon (POC) and total chlorophyll a (Chl a). Two different approaches have been adopted. The first approach was to use the available empirical material (the results of field measurements and laboratory analyses of discrete water samples) and find statistical formulas for estimating the biogeochemical properties of suspended particulate matter from those of inherent optical properties (IOPs), which are potentially retrievable from remote sensing measurements. The second approach was to find formulas that would enable biogeochemical properties of suspended particulate matter to be estimated directly from spectral values of the remote-sensing reflectance Rrs. The latter was based on statistical analyses of a synthetic data set of Rrs obtained from numerical simulations of radiative transfer for which the available empirical material on seawater IOPs and biogeochemistry served as input data. Among the empirical formulas based on seawater IOPs that could be used as a step in two-stage remote sensing algorithms (the other step is estimating certain IOPs from reflectance), the best error statistics are found for estimates of SPM and POM from the particulate backscattering coefficient bbp in the blue region of light wavelengths (443nm), and for estimates of POC and Chl a from the coefficient of light absorption by the sum of all non-water (i.e. suspended and dissolved) constituents of seawater an, in the blue (443nm) and green (555nm) parts of the spectrum respectively. For the semi-empirical formulas under consideration, which could serve as starting points in the development of local onestage (direct) remote sensing algorithms, the best error statistics are found when SPM, POM and POC are estimated from the same blue-to-red band reflectance ratio (Rrs(490)/Rrs(645)) (with estimated SPM reaching a better precision than estimated POM and POC), and when Chl a is estimated from the green-to-red band ratio (Rrs(555)/Rrs(645)).

An optical model for deriving the spectral particulate backscattering coefficients in oceanic waters

Abstract. An optical model is developed based on the diffuse attenuation coefficient (Kd) to estimate particulate backscattering coefficients bbp(λ) in oceanic waters. A large in situ data set is used to establish robust relationships between bbp(530) and bbp(555) and Kd(490) using an efficient nonlinear least-square method which uses the trust region algorithm with Bisquare weights scheme to adjust the coefficients. These relationships are obtained with good correlation coefficients (R2 = 0.786 and 0.790), low root mean square error (RMSE = 0.00076 and 0.00072) and 95% confidence bounds. The new model is tested with three independent data sets: the NOMAD SeaWiFS Match ups, OOXIX IOP algorithm workshop evaluation data set (Version 2.0w APLHA), and IOCCG simulated data set. Results show that the new model makes good retrievals of bbp at all key wavelengths (from 412–683 nm), with statistically significant improvements over other inversion models. Thus, the new model has the potential to improve our present knowledge of particulate matter and their optical variability in oceanic waters.

Comparison of SeaWiFS and MODIS time series of inherent optical properties for the Adriatic Sea

Abstract. Time series of inherent optical properties (IOPs) derived from SeaWiFS and MODIS are compared for the Adriatic Sea. The IOPs are outputs of the Quasi-Analytical Algorithm and include total absorption a, phytoplankton absorption aph, absorption associated with colored detrital material (CDM) acdm, and particle backscattering coefficient bbp. The average root-mean square difference Δ computed for log-transformed distributions decreases for $a$ from 0.084 at 412 nm to 0.052 at 490 nm, is higher for aph(443) (0.149) than for acdm(443) (0.071), and is approximately 0.165 for bbp at various wavelengths. The SeaWiFS a at 443 and 490 nm, aph at 443 nm and bbp are on average higher than the MODIS counterparts. Statistics show significant variations in space and time. There is an overall increasing gradient for Δ associated with the absorption terms from the open southern and central Adriatic to the northwest part of the basin, and a reversed gradient for the particulate backscattering coefficient. For time series analysis, only a(412) and acdm(443) currently present an unbiased continuity bridging the SeaWiFS and MODIS periods for the Adriatic Sea.

Retrieval of inherent optical properties of the Yellow Sea and East China Sea using a quasi-analytical algorithm

We tested and modified the quasi-analytical algorithm (QAA) using 57 groups of field data collected in the spring of 2003 in the Yellow Sea and East China Sea. The QAA performs well in deriving total absorption coefficients of typical coastal waters. The average percentage difference (APD) is in a range of 13.9%–38.5% for the total absorption coefficient (13.9% at 440 nm), and differences in particle backscattering coefficient bbp(λ) are less than 50% (in the case of the updated QAA). To obtain improved results, we modified the QAA by adjusting the empirical relationships. The modified algorithm is then applied to the field data to test its performance. The APDs were 44.7%–46.6% for bbp(λ) and 9.9%–32.8% (9.9% at 555 nm) for the total absorption coefficient. This indicates that the modified QAA derives better results. We also used the modified model to derive phytoplankton pigment absorption (aph) and detritus and CDOM absorption (adg) coefficients. The APDs for aph and adg at 440 nm are 37.1% and 19.8%. In this paper, we discuss error sources using the measured dataset. More independent field data can improve this algorithm and derive better results.

Satellite retrieval of inherent optical properties in the turbid waters of the Yellow Sea and the East China Sea

In situ-satellite match-ups of radiometric data are established in the turbid waters of the Yellow Sea and the East China Sea. Inherent optical properties (IOPs) are retrieved by match-up radiometric data and multi-band quasi-analytical algorithm (QAA). By comparing in situ spectra-retrieved IOPs with the satellite ones of moderate resolution imaging spectroradiometer (MODIS) and medium resolution imaging spectrometer (MERIS), the accuracy of satellite-derived IOPs is quantified. The median of the absolute percentage difference is found to be approximately 20% for the total absorption coefficient at(\lambda) at green and blue-green bands, and 30% for particulate material backscattering coefficient bbp(\lambda) throughout the visible bands. The spatial pattern and temporal variability of IOPs along the eastern coast of China are clarified based on satellite images and the QAA model.

Variability of the relationship between the particulate backscattering coefficient and the volume scattering function measured at fixed angles

The particulate backscattering coefficient bbp is an inherent optical property that plays a central role in studies of ocean color remote sensing. Because of practical difficulties associated with measurements of the volume scattering function (VSF) over the whole backward hemisphere, bbp is currently derived using fixed‐angle backscattering sensors and applying a conversion factor for particulate backscattering, referred to as χp. The underlying assumptions of the fixed‐angle approach are as follows: (1) in the green band, χp is fairly constant in the angular range 100°–150° and (2) for a fixed scattering angle, χp is wavelength‐independent. In this study we investigated the variability of χp based on spectral measurements of the full VSF, both in situ and for algal culture in the laboratory. The in situ data used in our study were acquired in a coastal environment outside of phytoplankton blooms, whereas the laboratory data were representative for phytoplankton bloom conditions in oceanic waters. At 555 nm, χp was found to vary significantly in the angular range 100°–130°, and at 140°, χp was found to be weakly variable in nonblooming waters only. The spectral variability of χp was studied for the first time, and the spectral slopes of χp, measured in situ, were found to vary within ±6%. Under the assumption that χp(140°) is wavelength‐independent, the induced error in the estimates of bbp was found to be lower than 10%. The algal culture showed a much higher spectral variability in χp(±20%), which induced an error in the estimates of bbp up to ±25.8%.

Optical properties of the particles in the Crimea coastal waters (Black Sea)

A field experiment was carried out in summer 2002 on an oceanographic platform near the coast of Crimea, in the Black Sea. For the first time, the spectral volume scattering function (VSF) was measured for a wide range of scattering angles (i.e., from 0.6 to 177.3 degrees) using a recently developed device. Our analysis revealed that the mineral particles are the primary component influencing the scattering and backscattering coefficient in the study area. The good correlation obtained between the backscattering coefficient bbp and the nonalgal particles absorption coefficient showed that the absorption efficiency of the mineral particles is high in the second half of the experiment. The ratio Chla/cp (where Chla is the chlorophyll a concentration and cp is the beam attenuation coefficient) did not correlate with the backscattering ratio and thus could not be used in this experiment as an alternative proxy to estimate the bulk composition of the particles. The spectral variation of bp (the scattering coefficient) and bbp (the backscattering coefficient) was less steep than what can be found in the open ocean waters. That was explained by the influence of the absorption on the scattering process, especially in the blue, as a consequence of the anomalous dispersion. The average backscattering ratio bp varied spectrally within 4%. Nevertheless, a high spectral variability of bp (around 30%) was observed suggesting that the use of a flat spectral variation is not accurate in coastal zones.